{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from duke_dbt_data import dcmread_image, read_boxes, draw_box"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "df = read_boxes(boxes_fp=\"/data/boxes-train.csv\", filepaths_fp=\"/data/file-paths-train.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "box_series = df.iloc[0]\n",
    "view = box_series[\"View\"]\n",
    "slice_index = box_series[\"Slice\"]\n",
    "# if you have image data saved in classic path folder structure, read the file path from \"classic_path\"\n",
    "# image_path = os.path.join(\"/data\", view_series[\"classic_path\"])\n",
    "image_path = os.path.join(\"/data\", box_series[\"descriptive_path\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.8/site-packages/openjpeg/utils.py:189: UserWarning: The (0028,0101) Bits Stored value '10' in the dataset does not match the component precision value '16' found in the JPEG 2000 data. It's recommended that you change the Bits Stored value to produce the correct output\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 12.5 s, sys: 160 ms, total: 12.7 s\n",
      "Wall time: 12.7 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "image = dcmread_image(fp=image_path, view=view, index=slice_index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y, width, height = box_series[[\"X\", \"Y\", \"Width\", \"Height\"]]\n",
    "image = draw_box(image=image, x=x, y=y, width=width, height=height, lw=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(image, cmap=plt.cm.gray);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
